Evaluation of Clinical Diagnosis Effect of Intracranial Aneurysms Combined with Artificial Intelligence Assistant Diagnosis System

Objectives: An intracranial aneurysm, usually referred to as an abnormal bulge in the wall of an intracranial artery, is the number one cause of subarachnoid hemorrhage and ranks third among cerebrovascular accidents after cerebral thrombosis and hypertensive cerebral hemorrhage. Subtraction Angiography (DSA) are currently common diagnostic methods. Artificial Intelligence (AI) is a new interdisciplinary, which can greatly help doctors diagnose and treat. Many researchers have contributed novel insights to the study of clinical diagnosis of intracranial aneurysms, which serves as the research direction and foundation of this paper. This study aims to explore how to use artificial intelligence technology to assist doctors in the diagnosis of intracranial aneurysms to improve the accuracy and sensitivity of diagnosis. Materials and Methods: This paper introduced the background of intracranial aneurysm and auxiliary diagnosis system and then carried out academic research and summary on the two key sentences of clinical diagnosis of intracranial aneurysm and the effect of AI auxiliary diagnosis system on clinical diagnosis of intracranial aneurysm. After that, the algorithm model was established and the algorithm was proposed to provide a theoretical basis for the analysis of clinical diagnosis effect of intracranial aneurysms combined with AI auxiliary diagnosis system. Next, the principles and technical methods of the basic theory were analyzed. At the end of the paper, the simulation experiment was carried out and the experiment was summarized and discussed. Results: A total of 50 patients with intracranial aneurysms were studied in clinical diagnosis. It can be seen that the accuracy and sensitivity of MRI (Magnetic Resolution Imaging) in detecting aneurysms were significantly different from those of CT (Computed Tomography) and DSA (Digital Subtraction Angiography); DSA was significantly superior to CT and MRI in the details and neck of the aneurysm and there was a significant difference between them. At the same time, with the research on the clinical diagnosis effect of intracranial aneurysms, the research on artificial intelligence assisted diagnosis system is also facing new opportunities and challenges. Conclusion: Intracranial aneurysms should be treated as soon as possible after diagnosis and the judgment rate of DSA for intracranial aneurysms is high.